## Course Information

## Description

This 4-day course offers a compact introduction to mathematical optimization aimed at young researchers. We invite researchers in non-mathematical fields as well as in mathematics to attend the classes. The goal of the course is to enable the participants to recognize the characteristics of a given optimization problem, to understand its difficulties and limitations, and to choose suitable solution methods as well as to develop ideas on how to model problems from their own field as optimization problems.

## Program

On each of the four days from **March 27-30 2023**, we will focus on one of the following four categories of optimization problems:
day 1) unconstrained optimization
day 2) convex optimization
day 3) nonlinear optimization
day 4) infinite-dimensional optimization

For each of these problem classes, we will study meaningful examples, the relevant theory and prominent solution algorithms.
Every day consists of a 90-minute lecture part in the morning (**10:00am-12:00 pm**) and a 90-minute hands-on exercise session in the afternoon (**1:00-3:00 pm**).
For the hour-long break 12:00-1:00 pm, we would like to invite the participants to join us at the nearby
Bräustadl for lunch.

## Credit and Registration

**Registration is required!**
Please register via
email to the office of the graduate school
.
You can find additional information such as on credit points at the
website of the HGS.

## Content

### Lecture notes

- Lecture notes (2023-03-27)
- Lecture notes (2023-03-28)
- Lecture notes (2023-03-29)
- Lecture notes (2023-03-30)

### Additional material for lectures

Some solutions use CasADi.

- Solution of the Rosenbrock example using CasADi (problem-based)
- Solution of the Rosenbrock example using CasADi (Opti interface-based)
- Solution of the airplane example using CasADi (problem-based)
- Create the matrix of differences for total-variation image denoising
- Rudimentary Chambolle-Pock algorithm